Unmanned vehicles (UVs), including unmanned aerial vehicles (UAVs) and ground vehicles (UGVs) are increasingly becoming more sophisticated and reliable for various military operations. They are also becoming smaller and less costly to produce. While many missions were already carried out with UAVs and/or UGVs, they were usually focused on a single UV at a time.
The affordability of concurrently deploying a fleet (e.g., tens or hundreds) of UVs is expected to be achieved in the near future. However, an important aspect of such realization relies heavily on the collaborative operation between the deployed UVs, particularly on the battlefields.
One such obvious collaborative operation of UVs is focused on persistent surveillance. It is projected that in the future, persistent surveillance by UVs will play a critical role in eliminating human casualties while simultaneously enhancing the quality of such operations.
As a result, it would be desirable to optimize the fleet of UVs for loitering patterns as well as for their maintenance scheduling, in order to maximize coverage of the given area of surveillance, by minimizing unnecessary overlaps. In other terms, for a given fleet of UVs with different mission payloads and characteristics, specified areas of interest, and a given set of maintenance sites, it would be desirable to find an optimum set of loitering routes along with the optimal maintenance schedule that maximizes coverage (i.e., minimizes the surveillance overlap).
UV maintenance also represents a concern for the operation. Typically, a UV needs to be recharged or refueled within a few hours, although there exists UVs that can operate for a much longer time. This means that typically after one or two hours of loitering, a given UV must land at a designated maintenance point to refuel or recharge. Although for a UGV, the refueling time might somewhat be greater on the average than that of an UAV, the underlying principle remains the same for these UVs.
What is therefore needed is an advanced optimization framework for air-ground persistent surveillance using unmanned vehicles. Prior to the advent of the present invention, the need for such an optimization framework has heretofore remained unsatisfied.